Modern high performance ultrasound imaging systems are currently used for medical applications and other uses. Generally, such systems employ a sonic transducer to emit a sonic pulse through a medium, such as the human body, which generates sonic echoes. These echoes are received by the transducer or other sensors and captured in data that is stored and ultimately used to generate images on a display. Measurements are then taken from the display. In some systems the measurements are taken with such hand-held tools as rulers and calipers. Other systems incorporate electronic measurement tools into the display.
The information measurable from the display depends on the operational mode of the ultrasound image. Current ultrasound systems allow the use of several operational modes, including a two-dimensional (2-D) mode (also sometimes referred to as "B-mode"), a Doppler mode, and a motion mode (M-mode). Each of these operational modes allows the ultrasound system user to obtain different ultrasound measurements: the 2-D mode allows the user to measure distances, areas and volumes directly from the display. The Doppler mode allows the user to obtain measurements from the display that indicate velocities. The M-mode allows the user to measure the movement of structures in one-dimension over time.
In making a diagnosis from ultrasound images, physicians typically rely on adequate image quality, acquisition of proper views, and sufficient quantification of all relevant structures and flows. Although image quality is usually constant within a system and acquisition of proper views is typically associated with a standard protocol within each lab, quantification of all relevant information is particularly problematic. In present ultrasound systems, the user must have sufficient knowledge of the structures and flows associated with various diagnoses to interpret the results of the ultrasound measurements. Typically, the need for additional measurements and the type of additional measurements needed are determined by each user based on his or her knowledge and interpretation of the ultrasound views.
Some efforts have been made to automate ultrasound measurement systems. However, these efforts have still involved significant user interaction to interpret the views, to make decisions regarding the need for additional ultrasound measurements, and to make appropriate diagnoses.
Thus, a heretofore unaddressed need exists in the industry for an automatic ultrasound measurement system and method that reduces the necessary amount of user interaction by automatically analyzing ultrasound measurements to provide the user with a list of the most likely diagnoses and to recommend additional ultrasound measurements relevant to confirming the diagnosis.